Recoverable Identifier

arXiv:2605.18079 · detector doi_compliance · incontrovertible · 2026-05-20 11:52:28.045691+00:00

advisory doi_compliance recoverable_identifier

DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.1109/TPAMI.2018.2889473.Merrill) was visible in the surrounding text but could not be confirmed against doi.org as printed.

Paper page Integrity report arXiv Try DOI

Evidence text

URL https://openreview.net/forum ?id=FdkPOHlChS. Oral. Kitaev, N., Kaiser, L., and Levskaya, A. Reformer: The efficient transformer. In8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020. OpenReview.net, 2020. URL https://openreview.net/forum?id=rkgN KkHtvB. Li, Q. and Wang, Y . Constant bit-size transformers are Turing complete. InAdvances in Neural Information Processing Systems, 2025. URL https://openrevi ew.net/forum?id=RBWnyDEBKf. Li, Q. and Wang, Y . Efficient Turing machine simula- tion with transformers. InThe Fourteenth International Conference on Learning Representations, 2026. URL https://openreview.net/forum?id=bxVu ILo1xx. Li, Z., Liu, H., Zhou, D., and Ma, T. Chain of thought em- powers transformers to solve inherently serial problems. InThe Twelfth International Conference on Learning Rep- resentations, 2024. URL https://openreview.n et/forum?id=3EWTEy9MTM. Liu, B., Ash, J. T., Goel, S., Krishnamurthy, A., and Zhang, C. Transformers learn shortcuts to automata. InThe Eleventh International Conference on Learning Repre- sentations, 2023. URL https://openreview.net /forum?id=De4FYqjFueZ. Liu, D., Chen, M., Lu, B., Jiang, H., Han, Z., Zhang, Q., Chen, Q., Zhang, C., Ding, B., Zhang, K., Chen, C., Yang, F., Yang, Y ., and Qiu, L. RetrievalAttention: Accelerating long-context LLM inference via vector retrieval. InAd- vances in Neural Information Processing Systems, 2025. URL https://openreview.net/forum?id= 8

Evidence payload

{
  "printed_excerpt": "URL https://openreview.net/forum ?id=FdkPOHlChS. Oral. Kitaev, N., Kaiser, L., and Levskaya, A. Reformer: The efficient transformer. In8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, ",
  "reconstructed_doi": "10.1109/TPAMI.2018.2889473.Merrill",
  "ref_index": 8,
  "resolved_title": null,
  "verdict_class": "incontrovertible"
}